R'ers:
I was hoping I could get some direction on this. I have a dataset
of the form:
Y1,Y2,...,YM = f(X1,X2,...,XN), where N is >>> M
The response data (Y1,Y2,...,YM) is frequency data, such that the sum of
all Yi = 1.0. Both Xj and Yi are continuous variables.
I'm trying to figure out the best approach(es) to solving for the model
f() -- any ideas? I could solve each Y one at a time, but the lack of
constraint worries me, and I'm pretty sure that normalizing the data
afterwards to sum to 1.0 is not going to work out properly. Thoughts?
I've never worked with multiple response statistics before, so I'm
mostly trying to get some pointers on where to begin investigating...
--j
--
Jonathan A. Greenberg, PhD
Postdoctoral Scholar
Center for Spatial Technologies and Remote Sensing (CSTARS)
University of California, Davis
One Shields Avenue
The Barn, Room 250N
Davis, CA 95616
Cell: 415-794-5043
AIM: jgrn307, MSN: jgrn...@hotmail.com, Gchat: jgrn307
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
